Dynamic switched crowding-based multi-objective particle swarm optimization algorithm for solving multi-objective AC-DC optimal power flow problem-Reference-Cited by-同舟云学术

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Dynamic switched crowding-based multi-objective particle swarm optimization algorithm for solving multi-objective AC-DC optimal power flow problem

Published:2024-11 Issue: Volume:166 Page:112155
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Bakır Hüseyin,Kahraman Hamdi Tolga,Yılmaz Samet,Duman Serhat^ORCID,Guvenc Ugur^ORCID

Publisher

Elsevier BV

Reference82 articles.

1. Review and comparison of genetic algorithm and particle swarm optimization in the optimal power flow problem;Papazoglou;Energies,2023

2. Development of the multi-objective adaptive guided differential evolution and optimization of the MO-ACOPF for wind/PV/tidal energy sources;Duman;Appl. Soft Comput.,2021

3. A modified teaching–learning based optimization for multi-objective optimal power flow problem.;Shabanpour-Haghighi;Energy Convers. Manag.,2014

4. Multi-objective optimal power flow with stochastic wind and solar power;Li;Appl. Soft Comput.,2022

5. Optimal power flow solutions using differential evolution algorithm integrated with effective constraint handling techniques;Biswas;Eng. Appl. Artif. Intell.,2018

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